基于二代Curvelet和PCA变换的遥感影像融合  

Remote Sensing Image Fusion Based on Second Curvelet and PCA Transform

作　　者：赵心[1] 

机构地区：[1]山东科技大学资源与土木工程系,泰安271000

出　　处：《科学技术与工程》2012年第3期581-585,共5页Science Technology and Engineering

基　　金：山东科技大学"春蕾计划"项目(2008BZC056)资助

摘　　要：提出了一种基于二代Curvelet变换和PCA变换的图像融合方法。首先对低分辨率多光谱图像进行PCA变换得到各个主成分,然后对高分辨率图像和低分辨率图像的前三个主分量进行Curvelet变换,并进行系数调整实现融合。最终得到PCA反变换后的融合图像。经实验结果表明,该方法有效,优于传统的融合方法。A new image fusion algorithm based on principal component analysis（PCA） and second curvelet transform is proposed.Firstly PCA transform is applied to low resolution multi-spectral image and principal components are obtained.Secondly curvelet transform is respectively applied to high resolution image and the first three principal components of the low resolution image and then merged with coefficient adjustment.Finally the fused result is obtained by inverse PCA transform.The experimental results illustrate that the algorithm is effective than other traditional methods.

关 键 词：主成分分析 二代Curvelet变换 融合 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]